u/Agile-Act2855

I’m seeing a lot of noise around GEO / AEO after Google’s AI Mode and AI Overviews updates.

My current take is: GEO is not a separate magic channel. It’s mostly SEO, but the audit process needs to change.

Instead of only asking “does this page rank?”, we also need to ask:

1. Can AI systems clearly understand what this page is about?
2. Can they identify the brand, product, service, audience, and proof?
3. Would this page be easy to summarize or cite?
4. Which competitors are being cited instead?
5. Are the claims, examples, FAQs, comparisons, and evidence clear enough?

So maybe the real shift is not SEO → GEO.

It’s: ranking audit → visibility + citation + clarity audit.

Curious how others here are thinking about this. Are you actually changing your SEO process because of AI Mode / AI Overviews, or is this mostly hype?

GEO / AI search visibility still feels vague to a lot of people, and I think part of the problem is that people jump straight to “AI visibility scores” before defining what should actually be audited.

I’m trying to think about it less as a separate magic layer and more as an extension of SEO:

Can AI systems clearly understand, retrieve, summarize, and cite your site?

Here’s what I’d include in a practical AI search visibility audit:

1. Prompt testing Run realistic buyer/research prompts across ChatGPT, Gemini, Perplexity, Copilot, etc. Not just “best X,” but comparison, problem-aware, and alternative-seeking prompts.

2. Citation checks Which pages get cited? Which competitors get cited instead? Are the cited pages actually the best pages, or just the easiest ones to parse?

3. Entity clarity Can the site clearly explain who it is, what it offers, who it serves, and how it is different?

4. Page structure Are key pages easy to summarize? Do they answer direct questions? Are headings, FAQs, comparisons, use cases, and evidence easy to extract?

5. Competitor comparison For the same prompts, which competitors appear more often, and what content formats are helping them?

6. Rewrite recommendations Not “stuff more keywords,” but rewrite pages so claims are clearer, use cases are explicit, and evidence is easier to cite.

7. Measurement Use whatever is available: referral traffic, server logs, Bing/Clarity-style citation data, Search Console changes, and manual prompt snapshots. None of these are perfect, but together they give direction.

My current view: AI search visibility is becoming more practical, but the audit should stay grounded in SEO fundamentals: crawlability, clear entities, useful content, structured pages, and external evidence.

What would you add or remove from this checklist?

Google says llms.txt isn’t needed for generative AI search, but at the same time it’s pushing UCP and agent-friendly website guidance.

That makes me wonder if we’re focusing on the wrong layer.

A lot of AEO/GEO advice is still about helping LLMs read or cite content.

But agentic search feels different. The bigger question may be:

Can an agent understand your site, navigate it, trust the data, and complete a task?

That shifts attention toward entity structure, feeds, semantic HTML, accessibility tree, structured actions, stable workflows, and clear agent policies.

Not saying UCP is a ranking factor. But it feels like a stronger signal than llms.txt about where the web is going.

Are you implementing llms.txt, or prioritizing agent-ready structure instead?

I think AI search optimization is moving from “answer visibility” to “execution readiness.”

A lot of AEO/GEO advice still sounds like: write clear content so ChatGPT/Perplexity can mention you.

But if Search is becoming more agentic, the real question may be:

Can an agent understand your site, trust the page, navigate the workflow, and complete a task?

That changes what matters: entity clarity, schema, internal links, comparison pages, accessible UI, stable layouts, crawlable flows, and content that explains not just “what this is” but “what can be done here.”

Not saying Lighthouse’s new Agentic Browsing checks are a ranking factor. But they do feel like a hint about where optimization is heading.

Are you already preparing sites for agentic browsing, or still mostly focused on AI citations?

I keep seeing people talk about llms.txt for AI SEO / GEO.

The idea makes sense in theory: give AI crawlers a simple file that explains which pages matter.

But right now it feels pretty unclear.

Google says it doesn’t use llms.txt for Search. There’s no proven ranking benefit. And I don’t think most SaaS teams should spend serious time on it.

That said, it’s also cheap to add.

My current take:

I wouldn’t make it a “project”.

But if it takes under an hour, I’d probably add a simple version with only:

• homepage
• pricing
• docs
• comparison pages
• use-case pages
• integration pages

I would not include every blog post or expect traffic from it.

Mostly, I see it as a low-cost experiment and a way to clarify which pages are actually important.

So for me:

Not urgent. Not proven. Probably worth a tiny test if your site already has strong product/docs pages.

Curious what others are doing.

Are you adding llms.txt, ignoring it, or waiting for clearer evidence?

Hi everyone, I’m looking for subreddits where people have thoughtful discussions about ecommerce SEO, Shopify growth, product discovery, and how AI search tools might affect online stores.

I’m not looking to promote anything or ask people to try a tool. I’m more interested in learning from store owners, marketers, and operators who discuss things like:

• product pages and SEO
• Shopify growth challenges
• schema / structured data
• how small ecommerce brands get discovered
• whether people are starting to use ChatGPT or Perplexity for product recommendations

Are there any good communities for this kind of discussion?

I’ve seen r/ecommerce and r/shopify, but I’m not sure where new users can participate respectfully without running into strict promo filters.

Thanks!

Hi everyone, I’m fairly new to Reddit and still learning how different communities work.

I recently tried to comment in a niche business subreddit, but my comment was removed because my post karma was too low. I understand why communities have filters, and I don’t want to spam or farm karma.

What are some good ways to build post karma properly?

I’m especially interested in:

• how to choose beginner-friendly subreddits
• what kind of posts are usually welcomed from new users
• what mistakes make new accounts look spammy
• whether it’s better to comment first or make simple discussion posts

I’d appreciate any advice from people who have been through this. Thanks!